A three-marker protein biosignature distinguishes tuberculosis from other respiratory diseases in Gambian children

EBioMedicine

Marie P. Gomez¹  Abdou K. Sillah²  Francis Mendy³  Schadrac C. Agbla⁴  Beate Kampmann⁵  Clive J. Hoggart⁵  Binta Saidy⁶  Uzochukwu Egere⁷  Madhukar Pai⁸  Toyin Togun⁸ 

[1] Corresponding author.;Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, New York, USA;Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, United Kingdom;The Vaccine Centre, and Clinical Research Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, United Kingdom;Tropical Medicine, Atlantic Boulevard, Fajara, The Gambia;Department of Health Data Sciences, University of Liverpool, Liverpool, United Kingdom;Section of Paediatrics, Imperial College London, St Mary's Campus, London, United Kingdom;;Vaccines and Immunity Theme, Medical Research Council Unit The Gambia at the London School of Hygiene &

关键词: Children;    Tuberculosis;    Cytokine;    Biosignature;    Diagnosis;   

DOI  :  

来源: DOAJ

【 摘 要 】

Background: Our study aimed to identify a host cytokine biosignature that could distinguish childhood tuberculosis (TB) from other respiratory diseases (OD). Methods: Cytokine responses in prospectively recruited children with symptoms suggestive of TB were measured in whole blood assay supernatants, harvested after overnight incubation, using a Luminex platform. We used logistic regression models with Least Absolute Shrinkage and Selection Operator (LASSO) penalty to identify the optimal biosignature associated with confirmed TB disease in the training set. We subsequently assessed its performance in the test set. Findings: Of the 431 children included in the study, 44 had bacteriologically confirmed TB, 60 had clinically diagnosed TB while 327 had OD. All children were HIV-negative. Application of LASSO regression models to the training set (n = 260) resulted in the combination of IL-1ra, IL-7 and IP-10 from unstimulated samples as the optimally discriminant cytokine biosignature associated with bacteriologically confirmed TB. In the test set (n = 171), this biosignature distinguished children diagnosed with TB disease, irrespective of microbiological confirmation, from OD with area under the receiver operator characteristic curve (AUC) of 0•74 (95% CI: 0•67, 0•81), and demonstrated sensitivity and specificity of 72•2% (95% CI: 60•4, 82•1%) and 75•0% (95% CI: 64•9, 83•4%) respectively, with its performance independent of their age group and their age- and sex-adjusted nutritional status. Interpretation: This novel biosignature of childhood TB derived from unstimulated supernatants is promising. Independent validation with further optimisation will improve its performance and translational potential. Funding: Steinberg Fellowship (McGill University); Grand Challenges Canada; MRC Program Grant.

【 授权许可】

Unknown